Prognostic nomogram of hypoxia-related genes predicting overall survival of colorectal cancer–Analysis of TCGA database

Lee, Joon Hyop; Jung, Sua; Park, Won Seo; Choe, Eun Kyung; Kim, Eun Young; Shin, Rumi; Heo, Seung Chul; Lee, Jae Hyun; Kim, Kwangsoo; Chai, Young Jun

doi:10.1038/s41598-018-38116-y

Cited by 37 publications

(32 citation statements)

References 42 publications

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“…Accordingly, these findings highlight a new insight into how KLK10 facilitates the development of CRC, supporting a potential avenue for the treatment of CRC. The hypoxic microenvironment is a proverbial feature of locally advanced solid tumors including CRC and constitutes a critical contributor to cancer development and survival outcomes [29,30]. Thus, we will explore the function of KLK10 in CRC cells under hypoxia conditions in our next plan.…”

Section: Discussionmentioning

confidence: 99%

Kallikrein-related peptidase (KLK10) cessation blunts colorectal cancer cell growth and glucose metabolism by regulating the PI3K/Akt/mTOR pathway

Wei

Dong

Shen

2020

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Colorectal cancer (CRC) is a common aggressive carcinoma with a proverbial feature of metabolic reprogramming that is essential for cancer cell growth. Recent research corroborates the controversial function of kallikrein-related peptidase 10 (KLK10) in cancer. However, its role and underlying mechanism in CRC remains elusive. In the present study, high expression of KLK10 was detected in CRC cell lines. Knockdown of KLK10 expression by a specific siRNA inhibited cell proliferation, evoked cell apoptosis, and increased caspase-3 activity in HT29 CRC cells. Furthermore, KLK10 suppression also afforded the suppressive effects on glycolysis in CRC cells as the data showed that targeting KLK10 restrained glucose uptake, lactate production, and glycolysis-related glucose transporter 1 (Glut1) expression. Mechanism analysis corroborated that cessation of KLK10 muted the PI3K/AKT-mTOR signaling. Intriguingly, reactivating the PI3K/AKT-mTOR pathway by its agonist IGF-1 notably reversed the inhibitory effects of KLK10 cessation on CRC cell growth and glucose metabolism. More important, preconditioning with PI3K/AKT inhibitor LY294002 or mTOR inhibitor rapamycin both aggravated KLK10 knockdown-suppressed cancer cell growth and glucose metabolism. These findings suggest that KLK10 silencing may attenuate the progression of CRC by inhibiting cell growth and glycolysis via the PI3K/AKT/mTOR signaling, supporting a potential and promising target for CRC therapy.

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Section: Discussionmentioning

confidence: 99%

Kallikrein-related peptidase (KLK10) cessation blunts colorectal cancer cell growth and glucose metabolism by regulating the PI3K/Akt/mTOR pathway

Wei

Dong

Shen

2020

neo

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“…Geisler et al (45) found that UBE2D2-mediated autophagy is involved in the progression of Parkinson's disease. Lee et al (46) found that the expression of UBE2D2 is associated with the prognosis of patients with colorectal cancer (CRC), suggesting that UBE2D2 could be used as one of the prognostic indicators of CRC. Peng et al (47,48) argued that autophagy involved with UBE2D2 has a significant impact on the internal environment and can promote the formation and degradation of ubiquitinated aggregates through autophagy.…”

Section: Discussionmentioning

confidence: 99%

Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke

et al. 2020

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Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.

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“…Our goal is to generate simple and effective prognostic tools based on several genes and other factors that may affect RFS (10). Using the TCGA dataset, we selected 7 genes by robust likelihood-based survival modeling and built a risk score system (11). We used an independent dataset (GSE76427) to validate the effectiveness of the risk score system, demonstrating that its clinical value for predicting RFS in HCC patients is better than that of the TNM staging system.…”

Section: Given the Remarkable Development Of High-throughput Technolomentioning

confidence: 99%

A prognostic model for predicting recurrence-free survival in hepatocellular carcinoma patients

Wang

Xie

et al. 2020

Preprint

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Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. Using the The Cancer Genome Atlas （TCGA） dataset, we identified genes that are associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. We identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. Validation in both the TCGA cohort and the GEO cohort demonstrated that the 7-gene prognostic model has the capability of predicting the RFS of HCC patients. Meanwhile, the result of multivariate Cox regression showed that the 7-gene prognostic model could work as an independent prognostic factor. In addition, according to the time dependent ROC curve, the 7-gene prognostic model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. What’s more, these seven genes were found to be related to the occurrence and development of liver cancer by exploring other three databases. Our study identified a seven-gene signature for HCC RFS prediction that is a novel and convenient prognostic tool. The seven genes might provide potential target genes for metabolic therapy and the treatment of HCC.

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Prognostic nomogram of hypoxia-related genes predicting overall survival of colorectal cancer–Analysis of TCGA database

Cited by 37 publications

References 42 publications

Kallikrein-related peptidase (KLK10) cessation blunts colorectal cancer cell growth and glucose metabolism by regulating the PI3K/Akt/mTOR pathway

Kallikrein-related peptidase (KLK10) cessation blunts colorectal cancer cell growth and glucose metabolism by regulating the PI3K/Akt/mTOR pathway

Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke

A prognostic model for predicting recurrence-free survival in hepatocellular carcinoma patients

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